The present invention relates generally to data communications networks and more particularly relates to a method for optimizing PNNI routing decisions over multiple parameters utilizing fuzzy logic.
Currently, there is a growing trend to make Asynchronous Transfer Mode (ATM) networking technology the base of future global communications. ATM has already been adopted as a standard for broadband communications by the International Telecommunications Union (ITU) and by the ATM Forum, a networking industry consortium.
ATM originated as a telecommunication concept defined by the Comite Consulatif International Telegraphique et Telephonique (CCITT), now known as the ITU, and the American National Standards Institute (ANSI) for carrying user traffic on any User to Network Interface (UNI) and to facilitate multimedia networking between high speed devices at multi-megabit data rates. ATM is a method for transferring network traffic, including voice, video and data, at high speed. Using this connection oriented switched networking technology centered around a switch, a great number of virtual connections can be supported by multiple applications through the same physical connection. The switching technology enables bandwidth to be dedicated for each application, overcoming the problems that exist in a shared media networking technology, like Ethernet, Token Ring and Fiber Distributed Data Interface (FDDI). ATM allows different types of physical layer technology to share the same higher layerxe2x80x94the ATM layer.
ATM uses very short, fixed length packets called cells., The first five bytes, called the header, of each cell contain the information necessary to deliver the cell to its destination. The cell header also provides the network with the ability to implement congestion control and traffic management mechanisms. The fixed length cells offer smaller and more predictable switching delays as cell switching is less complex than variable length packet switching and can be accomplished in hardware for many cells in parallel. The cell format also allows for multi-protocol transmissions. Since ATM is protocol transparent, the various protocols can be transported at the same time. With ATM, phone, fax, video, data and other information can be transported simultaneously.
ATM is a connection oriented transport service. To access the ATM network, a station requests a virtual circuit between itself and other end stations, using the signaling protocol to the ATM switch. ATM provides the User Network Interface (UNI) which is typically used to interconnect an ATM user with an ATM switch that is managed as part of the same network.
The current standard solution for routing in a private ATM network is described in the Privale Network Node Interface (PNNI) Phase 0 and Phase 1 specifications published by the ATM Forum. The previous Phase 0 draft specification is referred to as Interin Inter-Switch Signaling Protocol (IISP). The goal of the PNNI specifications is to provide customers of ATM network equipment some level of multi-vendor interoperability.
As part of the ongoing enhancement to the ATM standard by work within the ATM Forum and other groups, the Private Network to Network Interface (PNNI) protocol Phase 1 has been developed for use between private ATM switches and between groups of private ATM switches. The PNNI specification includes two categories of protocols. The first protocol is defined for the distribution of topology information between switches and clusters of switches where the information is used to compute routing paths within the network. The main feature of the PNNI hierarchy mechanism is its ability to automatically configure itself within the networks in which the address structure reflects the topology. The PNNI topology and routing techniques are based on the well-known link state routing technique.
The second protocol is effective for signaling, i.e., the message flows used to establish point-to-point and point-to-multipoint connections across the ATM network. This protocol is based on the ATM Forum User to Network Interface (UNI) signaling with mechanisms added to support source routing, crankback and alternate routing of source SETUP requests in the case of bad connections.
With reference to the PNNI Phase 1 specifications, the PNNI hierarchy begins at the lowest level where the lowest level nodes are organized into peer groups. A logical node in the context of the lowest hierarchy level is the lowest level node. A logical node is typically denoted as simply a node. A peer group is a collection of logical nodes wherein each node within the group exchanges information with the other members of the group such that all members maintain an identical view of the group. When a logical link becomes operational, the nodes attached to it initiate and exchange information via a well known Virtual Channel Connection (VCC) used as a PNNI Routing Control Channel (RCC).
Hello messages are sent periodically by each node on this link. In this fashion the Hello protocol makes the two neighboring nodes known to each other. Each node exchanges Hello packets with its immediate neighbors to determine its neighbor""s local state information. The state information includes the identity and peer group membership of the node""s immediate neighbors and a status of its links to its neighbors. Each node then bundles its state information in one or more PNNI Topology State Elements (PTSEs) which are subsequently flooded throughout the peer group.
PTSEs are the smallest collection of PNNI routing information that is flooded as a unit among all logical nodes within a peer group. A node topology database consists of a collection of all PTSEs received, which represent that particular node""s present view of the PNNI routing topology. In particular, the topology database provides all the information required to compute a route from the given source node to any destination address reachable in or through that routing domain.
When neighboring nodes at either end of a logical link begin initializing through the exchange of Hellos, they may conclude that they are in the same peer group. If it is concluded that they are in the same peer group, they proceed to synchronize their topology databases. Database synchronization includes the exchange of information between neighboring nodes resulting in the two nodes having identical topology databases. A topology database includes detailed topology information about the peer group in which the logical node resides in addition to more abstract topology information representing the remainder of the PNNI routing domain.
During a topology database synchronization, the nodes in question first exchange PTSE header information, i.e., they advertise the presence of PTSEs in their respective topology databases. When a node receives PTSE header information that advertises a more recent PTSE version than the one that it has already or advertises a PTSE that it does not yet have, it requests the advertised PTSE and updates its topology database with the subsequently received PTSE. If the newly initialized node connects to a peer group then the ensuing database synchronization reduces to a one way topology database copy. A link is advertised by a PTSE transmission only after the database synchronization between the respective neighboring nodes has successfully completed. In this fashion, the link state parameters are distributed to all topology databases in the peer group.
Flooding is the mechanism used for advertising links whereby PTSEs are reliably propagated node by node throughout a peer group. Flooding ensures that all nodes in a peer group maintain identical topology databases. A short description of the flooding procedure follows. PTSEs are encapsulated within PNNI Topology State Packets (PTSPs) for transmission. When a PTSP is received its component PTSEs are examined. Each PTSE is acknowledged by encapsulating information from its PTSE header within the acknowledgment packet that is sent back to the sending neighbor. If the PTSE is new or of more recent origin then the node""s current copy, the PTSE is installed in the topology database and flooded to all neighboring nodes except the one from which the PTSE was received. A PTSE sent to a neighbor is periodically retransmitted until acknowledged.
Note that flooding is an ongoing activity wherein each node issues PTSPs with PTSEs that contain updated information. The PTSEs contain the topology databases and are subject to aging and get removed after a predefined duration if they are not refreshed by a new incoming PTSE. Only the node that originally originated a particular PTSE can re-originate that PTSE. PTSEs are reissued both periodically and on an event driven basis.
As described previously, when a node first learns about the existence of a neighboring peer node which resides in the same peer group, it initiates the database exchange process in order to synchronize its topology database with that of its neighbor""s. The database exchange process involves exchanging a sequence of database summary packets that contain the identifying information of all PTSEs in a node topology database. The database summary packet performs an exchange utilizing a lock step mechanism whereby one side sends a database summary packet and the other side responds with its own database summary packet, thus acknowledging the received packet.
When a node receives a database summary packet from its neighboring peer, it first examines its topology database for the presence of each PTSE described within the packet. If the particular PTSE is not found in its topology database or if the neighboring peer has a more recent version of the PTSE then the node requests the PTSE from the particular neighboring peer or optionally from another neighboring peer whose database summary indicates that it has the most recent version of the PTSE.
A corresponding neighboring peer data structure is maintained by the nodes located on either side of the link. The neighboring peer data structure includes information required to maintain database synchronization and flooding to neighboring peers.
It is assumed that both nodes on either side of the link begin in the Neighboring Peer Down state. This is the initial state of the neighboring peer for this particular state machine. This state indicates that there are no active links through the neighboring peer. In this state, there are no adjacencies associated with the neighboring peer either. When the link reaches the point in the Hello protocol where both nodes are able to communicate with each other, the event AddPort is triggered in the corresponding neighboring peer state machine. Similarly when a link falls out of communication with both nodes the event DropPort is triggered in the corresponding neighboring peer""s state machine. The database exchange process commences with the event AddPort which is thus triggered but only after the first link between the two neighboring peers is up. When the DropPort event for the last link between the neighboring peers occurs, the neighboring peer state machine will internally generate the DropPort last event closing all state information for the neighboring peers to be cleared.
It is while in the Negotiating state that the first step is taken in creating an adjacency between two neighboring peer nodes. During this step it is decided which node is the master, which is the slave and it is also in this state that an initial Database Summary (DS) sequence number is decided upon. Once the negotiation has been completed, the Exchanging state is entered. In this state the node describes is topology database to the neighboring peer by sending database summary packets to it.
After the peer processes the database summary packets, the missing or updated PTSEs can then be requested. In the Exchanging state the database summary packets contain summaries of the topology state information contained in the node""s database. In the case of logical group nodes, those portions of the topology database that where originated or received at the level of the logical group node or at higher levels is included in the database summary. The PTSP and PTSE header information of each such PTSE is listed in one of the node""s database packets. PTSEs for which new instances are received after the exchanging status have been entered may not be included in any database summary packet since they will be handled by normal flooding procedures.
The incoming data base summary packet on the receive side is associated with a neighboring peer via the interface over which it was received. Each database summary packet has a database summary sequence number that is implicitly acknowledged. For each PTSE listed, the node looks up the PTSE in its database to see whether it also has an instance of that particular PTSE. If it does not or if the database copy is less recent, then the node either re-originates the newer instance of the PTSE or flushes the PTSE from the routing domain after installing it in the topology database with a remaining lifetime set accordingly.
Alternatively, if the listed PTSE has expired, the PTSP and PTSE header contents in the PTSE summary are accepted as a newer or updated PTSE with empty contents. If the PTSE is not found in the node""s topology database, the particular PTSE is put on the PTSE request list so it can be requested from a neighboring peer via one or more PTSE request packets.
If the PTSE request list from a node is empty, the database synchronization is considered complete and the node moves to the Full state.
However, if the PTSE request list is not empty then the Loading state is entered once the node""s last database summary packet has been sent but the PTSE request list is not empty. At this point, the node now knows which PTSE needs to be requested. The PTSE request list contains a list of those PTSEs that need to be obtained in order to synchronize that particular node""s topology database with the neighboring peer""s topology database. To request these PTSEs, the node sends the PTSE request packet which contains one or more entries from the PTSE request list. The PTSE request list packets are only sent during the Exchanging state and the Loading state. The node can send a PTSE request packet to a neighboring peer and optionally to any other neighboring peers that are also in either the Exchanging state or the Loading state and whose database summary indicate that they have the missing PTSEs.
The received PTSE request packets specify a list of PTSEs that the neighboring peer wishes to receive. For each PTSE specified in the PTSE request packet, its instance is looked up in the node""s topology database. The requested PTSEs are subsequently bundled into PTSPs and transmitted to the neighboring peer. Once the last PTSE and the PTSE request list has been received, the node moves from the Loading state to the Full state. Once the Full state has been reached, the node has received all PTSEs known to be available from its neighboring peer and links to the neighboring peer can now be advertised within PTSEs.
A major feature of the PNNI specification is the routing algorithm used to determine a path for a call from a source user to a destination user. The routing algorithm of PNNI is a type of link state routing algorithm whereby each node is responsible for meeting its neighbors and learning their identities. Nodes learn about each other via the flooding of PTSEs described hereinabove. Each node computes routes to each destination user using the information received via the PTSEs to form a topology database representing a view of the network.
Using the Hello protocol and related FSM of PNNI, neighboring nodes learn about each other by transmitting a special Hello message over the link. This is done on a continual periodic basis. When a node generates a new PTSE, the PTSE is flooded to the other nodes within its peer group. This permits each node to maintain an up to date view of the network.
Once the topology of the network is learned by all the nodes in the network, routes can calculated from source to destination users. A routing algorithm commonly used to determine the optimum route from a source node to a destination node is the Dijkstra algorithm. The Dijkstra algorithm is used to generate the Designated Transit List which is the routing list used by each node in the path during the setup phase of the call. Used in the algorithm are the topology database (link state database) which includes the PTSEs received from each node, a Path List comprising a list of nodes for which the best path from the source node has been found and a Tentative List comprising a fist of nodes that are only possibly the best paths. Once it is determined that a path is in fact the best possible, the node is moved from the Tentative List to the Path List.
The algorithm begins with the source node (self) as the root of a tree by placing the source node ID onto the Path List. Next, for each node N placed in the Path List, N""s nearest neighbors are examined. For each neighbor M, the cost of the path from the root to N to the cost of the link from N to M is added. If M is not already in the Path List or the Tentative List with a better path cost, M is added to the Tentative List.
If the Tentative List is empty, the algorithm terminates. Otherwise, a search is performed for the entry in the Tentative List with the minimum cost. That entry is moved to the Path List and the examination step described above is repeated.
Currently, fuzzy logic systems are being used in more and more applications. Fuzzy logic, based on fuzzy set theory (a generalization of classical set theory), permits the operational and control laws of a system to be expressed linguistically using words. Many times, such a system out performs systems based on traditional mathematical approaches. The main strength of fuzzy set theory is that it performs well when dealing with imprecision.
In classical set theory, an item is either part of a set or is not, without any room for partial membership. Fuzzy logic permits partial set membership and permits gradual transitions between being a full member of a set and fully being not a member of a set. Fuzzy logic permits partial truth and partial falseness. For example, the statement. xe2x80x9cThe car is traveling fastxe2x80x9d can have a range of truthfulness, depending on the speed of the car. If the car is traveling 30 mph the statement may be 40% true but if it is traveling 50 mph it may be 70% true. Thus, the path from falseness to truth is gradual.
The degree to which a variable is a member of a set is denoted by a degree of membership variable. Each fuzzy logic input variable and each output variable has an associated degree of membership function. Membership varies from 0 to 1, inclusive, and is the degree (usually represented by xcexc) that is termed the truth value and represents the degree to which an assertion is true.
The PNNI protocol, widely implemented in ATM networks, performs source routing to from source to destination nodes. The routing algorithm in PNNI generates the data path, i.e., the VC, between the source and destination. The routing algorithm selects one or more optional or candidate routes to the destination based on a criteria such as number of hops to the destination. The routing algorithm then determines the best or optimum route from among a plurality of possible optional routes using an optimization technique that examines one or more metrics, attributes and/or parameters associated with each optional route. Note that a metric is defined as an entity that accumulates, e.g., CTD while an attribute is a property of the network, e.g., an address, link capacity, node attributes, etc.
The number of optimizations metrics and attributes can vary according to the algorithm and/or protocol in use. Ideally, more than just a few of these should be taken into consideration when selecting a route since a route is characterized by many metrics, attributes and parameters as the link load, cell delay, cell delay variation, etc. When the number of metrics, attributes and/or parameters is few, e.g., one or two, the solution to the routing problem is relatively simple. Numerous methods of resolving the best or optimum route are well known in the networking art. Such well known techniques include, but are not limited to, methods that utilize one or more weighted averages and method that optimize based on the shortest path from one point to another.
The task of finding the optimum route becomes much more complicated, however, when the number of optimization parameters becomes larger than one or two. In a large group of metrics, attributes and parameters, it is typically the case that the individual members of the group relate very little with each other with each having varying degrees of importance in the determination of the route. For example, consider determining the best or optimum route based on the consideration of ten metrics, attributes and parameters. Each one having a different importance to the optimization process and each being totally unrelated to the others in meaning.
Performing routing decisions based on this data becomes a very complicated mathematical problem especially when the decision models the metrics, attributes and parameters as a non linear system whose behavior varies with time.
The present invention is a method of determining the optimum route from a source node to a destination node in an ATM network. The method utilizes fuzzy logic processing to determine the optimum route based on a set of metrics that may or may not be related to each other. The invention utilizes well known fuzzy logic techniques to perform optimization and calculations based on intuitive rules rather then complex mathematical solutions.
As an example, the method of the invention can be applied to PNNI routing in ATM networks. The PNNI protocol functions to route the data path between the source and destination using source routing techniques. Various criteria are used by the routing algorithm to determine the optimum path. The method of the invention can be used by the routing algorithm to determine the optimum route when it is desired to optimize the route based on a large number of metrics, attributes and/or parameters. The example described hereinbelow considers a set of nine metrics for evaluating each proposed route.
The fuzzy logic processing is divided into two phases. Each phase has its own set of rules that the input data are applied to. The first set of rules are used to divide the metrics into a smaller number of groups wherein each group contains metrics that relate to each other in some way. Crisp output values are calculated for each of the resulting groups. These values are then input to the second phase set of rules. The outputs generated are defuzzified and a single crisp output value is obtained. The centroid and weighted-average techniques in combination with the membership function for the output values are used to perform defuzzification. The output value generated represents an indication of the link quality on a scale of 0 to 100, for example.
A different set of metrics is processed for each optional route being considered by the routing algorithm. For each set a link quality value is determined. Once processing for all candidate routes s complete, the route having the maximum link quality indication is chosen and the route is configured.
There is provided in accordance with the present invention a method of optimizing the routing from a source node to a destination node based on a plurality of metrics, the method comprising the steps of providing a membership function for each metric to be considered in the optimization, providing a membership function for each fuzzy output to be generated, fuzzifying a set of crisp input values corresponding to the plurality of metrics so as to yield a set of fuzzy input values, applying the set of fuzzy input values to a fuzzy logic rule base so to yield a set of fuzzy output values, defuzzifying the set of fuzzy output values so as to yield a crisp output value indicative of the link quality associated with a particular candidate route, repeating the steps of fuzzifying, applying and defuzzifying for each candidate route to be considered and selecting the route having a maximum link quality indication as a final routing decision.
The step of defuzzifying comprises the step of utilizing a centroid technique to obtain crisp values for each rule within the fuzzy logic rule base triggered by the set of fuzzy input values or may comprise the step of utilizing a weighted-average technique to obtain a single crisp value from a plurality of crisp values generated from rules within the fuzzy logic rule base triggered by the set of fuzzy input values.
The method further comprises the step of dividing the set of metrics into a plurality of groups, wherein each group corresponds to one or more metric and is represented by a single fuzzy input value. The method further comprises the step of implementing the selected route utilizing the metrics corresponding thereto. The fuzzy logic rule base may embody different weights assigned to individual metrics.
There is also provided in accordance with the present invention a method of optimizing the routing from a source node to a destination node based on a plurality of metrics, the method comprising the steps of providing a membership function for each metric to be considered in the optimization, providing a membership function for each fuzzy output to be generated, dividing the plurality of metrics into one or more groups, fuzzifying a set of crisp input values corresponding to each group of metrics so as to yield a first plurality of sets of fuzzy input values, applying each first set of fuzzy input values to a first fuzzy logic rule base so to yield a first set of fuzzy output values, each group having an associated different first fuzzy logic rule base, defuzzifying the first set of fuzzy output values so as to yield a first crisp output value, fuzzifying the first crisp output value of each group so as to yield a second plurality of sets of fuzzy input values, applying each second set of fuzzy input values to a second fuzzy logic rule base so to yield a second set of fuzzy output values, defuzzifying the second set of fuzzy output values so as to yield a second crisp output value indicative of the link quality associated with a particular candidate route, generating a crisp output value indicative of the link quality for each candidate route to be considered and selecting the route having a maximum link quality indication as a final routing decision.